Data and Reproducibility

Data and Reproducibility Policy

1. Introduction

Andalasian Livestock (ALive) is committed to promoting transparency, reliability, research integrity, and reproducibility in animal science and livestock research.

The journal recognizes that access to appropriate research data, clear methodological descriptions, and accurate reporting of analytical procedures are essential for the critical evaluation and verification of scientific findings.

Transparent research practices strengthen the credibility of published articles, facilitate independent verification, support responsible data reuse, and contribute to the advancement of knowledge in livestock production, animal nutrition, breeding, genetics, reproduction, health, welfare, and related disciplines.

This policy establishes the journal's expectations concerning research data availability, data sharing, documentation, data citation, methodological transparency, research reproducibility, and responsible data management.

The policy is informed by the Core Practices of the Committee on Publication Ethics (COPE), particularly those relating to data and reproducibility, research integrity, and the reliability of the scholarly record.

2. Description

2.1. Research Data

Research data refer to the information, observations, measurements, records, and materials collected, generated, or analyzed to support the findings of a scholarly study.

For research within the scope of Andalasian Livestock, research data may include:

Livestock growth and production performance records.
Feed intake, feed conversion, and nutrient digestibility measurements.
Animal reproduction and breeding records.
Genetic and genomic datasets.
Animal health and disease surveillance data.
Laboratory measurements and analytical results.
Animal welfare and behavioral observations.
Environmental and housing measurements.
Experimental treatment and control records.
Farm management and livestock production datasets.
Survey and interview data collected from farmers or livestock industry participants.
Statistical analysis files, computational scripts, models, and supporting documentation.

Research data may be quantitative, qualitative, experimental, observational, computational, or derived from secondary sources.

2.2. Research Reproducibility

Research reproducibility refers to the ability of independent researchers to evaluate and, where appropriate, obtain consistent analytical results using the reported data, methods, and computational procedures.

In this policy, two related concepts are recognized:

Computational reproducibility: The ability to obtain consistent analytical results using the original dataset, software, code, and specified analytical procedures.

Empirical replicability: The ability to conduct an independent study using sufficiently described research methods and assess whether comparable findings can be obtained.

The journal recognizes that biological variation, environmental conditions, animal characteristics, and experimental circumstances may affect outcomes in livestock research.

Accordingly, reproducibility does not imply that every independent experiment must produce identical numerical results.

2.3. Data Availability

Data availability refers to the extent to which research data and supporting materials can be accessed for verification, further analysis, or responsible reuse.

Data may be:

Publicly available through an appropriate repository.
Included as supplementary material.
Available from the corresponding author upon reasonable request.
Accessible only under defined conditions.
Restricted because of legitimate ethical, legal, confidentiality, or intellectual property considerations.

The applicable access arrangements must be described accurately and transparently.

2.4. Data Availability Statement

A Data Availability Statement is a declaration explaining whether and how the data supporting the findings of an article can be accessed.

It should identify the relevant repository, persistent identifier, supplementary files, access conditions, or legitimate restrictions.

3. Policy

3.1. General Principles

Andalasian Livestock encourages responsible data sharing and transparent reporting of research methods.

Authors are expected to maintain accurate research records and provide sufficient information to permit critical evaluation of their findings.

The journal supports the principle that research data should be made as accessible as reasonably possible while respecting legitimate ethical, legal, commercial, and confidentiality restrictions.

The journal does not require authors to disclose protected information unlawfully or to violate valid ethical approvals, consent agreements, or confidentiality obligations.

3.2. Data Availability Statement

As a proposed mandatory submission requirement, all original research articles submitted to Andalasian Livestock should include a Data Availability Statement.

The statement should clearly explain:

Whether data supporting the findings are available.
Where the data are stored.
How the data may be accessed.
Whether access is unrestricted or conditional.
Whether any ethical, legal, or confidentiality restrictions apply.

The statement should be included in the manuscript and published with the article.

For review articles or other manuscripts that do not generate or analyze new datasets, authors should provide an appropriate statement explaining why data sharing is not applicable.

3.3. Public Data Sharing

Authors are strongly encouraged to deposit datasets supporting their findings in appropriate, trusted repositories whenever legally and ethically permissible.

Publicly shared datasets should contain sufficient information to support interpretation and reasonable verification of the published findings.

Authors are encouraged to provide:

Data underlying the principal results, tables, and figures.
Relevant metadata and variable descriptions.
Data dictionaries or codebooks.
Experimental protocols, where appropriate.
Statistical analysis scripts or computational code.
Documentation necessary to understand the dataset.

Public sharing should be conducted responsibly, with appropriate consideration of data quality, permissions, and applicable restrictions.

3.4. Data Repositories

Authors are encouraged to use established repositories that support reliable access, appropriate metadata, and persistent identification.

Potential repository options include:

General-purpose repositories

Zenodo
Figshare
Dryad
Open Science Framework (OSF)

Discipline-specific repositories

NCBI Sequence Read Archive (SRA), where appropriate for sequencing data.
NCBI Gene Expression Omnibus (GEO), where appropriate for functional genomics data.
Other established repositories suitable for animal science, agricultural research, or biological datasets.

Institutional repositories

Repositories operated by recognized universities or research institutions may be used when they support suitable research data deposit and access.

The selected repository should be appropriate to the type of data and should comply with relevant ethical, legal, and institutional requirements.

Authors should provide a persistent identifier, accession number, or stable repository link whenever available.

The journal does not require authors to use a particular commercial repository service.

3.5. Data Citation

Datasets used or generated in the research should be appropriately acknowledged and cited.

Where available, dataset citations should include:

Creator or author.
Dataset title.
Year of publication or release.
Repository or publisher.
Version number, where relevant.
Persistent identifier, such as a DOI or accession number.

Authors must properly acknowledge datasets produced by other researchers or institutions.

Data reuse must comply with applicable licensing, attribution, ethical, and access requirements.

3.6. Transparency of Research Methods

Authors must describe their research methods with sufficient detail to permit scientific evaluation and reasonable attempts at replication.

For livestock and animal science research, relevant methodological information may include:

Animal Characteristics

Species, breed, age, sex, physiological status, initial body weight, and other characteristics relevant to the study.

Experimental Design

Experimental treatments, control groups, randomization procedures, experimental units, replication, sample size, and study duration.

Animal Management

Housing conditions, feeding practices, environmental conditions, animal handling, and relevant management procedures.

Measurements and Sampling

Sampling methods, measurement intervals, laboratory procedures, instruments, and analytical techniques.

Statistical Analysis

Statistical models, experimental units, assumptions, significance thresholds, analytical software, and procedures used to evaluate the data.

Ethical Compliance

Relevant animal research ethics approvals, permits, and welfare safeguards where required.

Authors should cite established methods appropriately and describe substantive modifications to previously published procedures.

3.7. Statistical Reporting and Analytical Reproducibility

Authors must report statistical methods accurately and in sufficient detail to permit critical assessment.

Where applicable, manuscripts should identify:

The experimental unit and number of independent replicates.
Sample size and the basis for its selection.
Statistical tests or models.
Fixed and random effects.
Procedures for handling missing observations.
Treatment of outliers and exclusions.
Assumption checking and model diagnostics.
Software names and versions.
Appropriate measures of uncertainty and variability.

Authors should distinguish biological replicates from technical replicates and avoid pseudoreplication.

Selective reporting or inappropriate exclusion of observations must not be used to misrepresent research findings.

3.8. Code, Software, and Computational Models

For studies involving statistical programming, bioinformatics, simulation, predictive modeling, machine learning, or other computational methods, authors are encouraged to share the relevant code and supporting documentation.

Shared materials should include, where appropriate:

Source code or analysis scripts.
Software names and versions.
Required libraries and dependencies.
Parameter settings.
Data processing procedures.
Instructions for executing the analysis.
Model specifications and relevant validation procedures.

Where code cannot be shared because of legitimate restrictions, authors should explain the limitation and provide sufficient methodological detail to support evaluation.

3.9. Research Data Integrity

Authors are responsible for ensuring that the research data underlying their manuscripts are accurate, authentic, and appropriately documented.

The following practices are prohibited:

Fabrication: Inventing observations, measurements, or research results.

Falsification: Manipulating data, experimental procedures, or analytical results in ways that misrepresent the research.

Selective Reporting: Deliberately excluding relevant results or observations to create a misleading interpretation.

Misrepresentation of Data Sources: Providing inaccurate information about the origin, collection, ownership, or processing of research data.

Inappropriate Data Manipulation: Altering images, laboratory records, or numerical datasets without appropriate scientific justification and disclosure.

Legitimate data cleaning, transformation, and exclusion procedures must be scientifically justified and reported transparently.

Suspected data misconduct will be addressed under the journal's Allegations of Misconduct Policy.

3.10. Restricted and Confidential Data

Andalasian Livestock recognizes that certain research datasets cannot be made publicly available.

Legitimate restrictions may arise from:

Confidentiality agreements with commercial livestock enterprises.
Personal information relating to farmers, employees, or research participants.
Confidential farm management or business records.
Protected veterinary or animal health information.
Biosecurity and animal disease reporting considerations.
Intellectual property or contractual obligations.
Ethical approval conditions.
Restrictions imposed by lawful data custodians.

Authors must disclose relevant restrictions in the Data Availability Statement.

Where feasible, authors should consider sharing anonymized, aggregated, or otherwise appropriately de-identified datasets.

The journal will not require public release of information when disclosure would violate applicable laws, legitimate agreements, or ethical obligations.

3.11. Data Involving Human Participants

Some livestock and agricultural research involves interviews, surveys, or observations of farmers, farm workers, veterinarians, or other participants.

Authors must ensure that data collection and sharing comply with applicable ethical approval, consent, confidentiality, and privacy requirements.

Personal identifiers should be removed or appropriately protected before data sharing.

Where consent does not permit public sharing, authors should explain the applicable access restrictions.

3.12. Animal Research Data and Ethical Oversight

Data sharing must not compromise the ethical treatment of animals or legitimate animal health and biosecurity requirements.

Authors should maintain sufficient records to support verification of animal experiments and compliance with applicable ethical approvals.

Where relevant, records should document animal allocation, treatments, observations, welfare monitoring, adverse events, and experimental outcomes.

Research data management must be consistent with the journal's Ethical Oversight Policy.

3.13. Data Retention

Authors and their institutions are responsible for retaining original research data and relevant documentation for a period consistent with applicable institutional policies, funding agreements, ethical approvals, and legal requirements.

Data should be stored securely and protected against unauthorized modification, loss, or disclosure.

Authors are encouraged to maintain sufficient records to respond to legitimate questions concerning the published research.

Specific minimum retention period: [INSERT VERIFIED INSTITUTIONAL OR JOURNAL REQUIREMENT, IF ADOPTED]

The journal does not prescribe an arbitrary universal retention period where no approved requirement has been established.

3.14. Access to Underlying Data During Peer Review

The editorial team may request access to underlying research data, analysis files, or supporting documentation when reasonably necessary to evaluate a manuscript.

Such requests may arise when:

Important results cannot be adequately evaluated.
Statistical analyses require clarification.
There are inconsistencies between reported findings and supporting information.
Questions arise concerning the authenticity or integrity of the data.
Additional information is necessary to assess methodological reliability.

Requests must be proportionate and must respect legitimate confidentiality and data protection restrictions.

Failure to provide reasonable clarification or verification may affect the editorial decision.

3.15. Data Availability and Publication Decisions

The availability and adequacy of supporting data may be considered during editorial assessment.

However, restricted access to research data does not automatically disqualify a manuscript from publication when the restrictions are legitimate, transparently disclosed, and compatible with adequate scientific evaluation.

The editorial team may request alternative verification arrangements when public data sharing is not possible.

The final decision must consider scientific validity, research integrity, ethical requirements, and the adequacy of the available evidence.

3.16. Registration of Studies and Research Protocols

Authors are encouraged to register research protocols or analysis plans when appropriate to the study design and relevant disciplinary standards.

Prospective registration may be particularly useful for certain intervention studies, systematic reviews, or other research designs where advance specification can reduce selective reporting.

The journal does not impose universal prospective registration on all livestock research.

Where a study has been registered, authors should provide the registration identifier and describe substantive deviations from the registered protocol.

3.17. Post-Publication Data Concerns

Concerns about the availability, authenticity, accuracy, or interpretation of data may arise after publication.

The journal will assess credible concerns and may request clarification, underlying data, analytical documentation, or relevant institutional findings.

Depending on the evidence, appropriate actions may include:

Correction: When a specific error can be corrected without invalidating the principal findings.

Expression of Concern: When substantial unresolved concerns warrant alerting readers.

Retraction: When the findings are unreliable or other circumstances meet applicable retraction criteria.

No Further Action: When the concern is unsupported or satisfactorily resolved.

Editorial responses will follow the journal's Allegations of Misconduct Policy and Post-Publication Discussions and Corrections Policy.

4. Implementation and Procedures

4.1. Data Availability Statement at Submission

As a proposed implementation requirement, authors should include a Data Availability Statement in every submitted original research manuscript.

The statement should be placed in a consistent location specified by the journal's manuscript template, preferably before the References section.

The editorial office should check for the statement during the initial submission screening.

4.2. Recommended Data Availability Statement Examples

A. Publicly Available Data

"The datasets generated and analyzed during the current study are publicly available in [Repository Name] at [DOI or Persistent URL]."

B. Data Available as Supplementary Material

"The data supporting the findings of this study are included in the article and its supplementary materials."

C. Data Available Upon Reasonable Request

"The datasets supporting the findings of this study are available from the corresponding author upon reasonable request."

D. Restricted Data

"The data supporting the findings of this study are not publicly available due to [specify legitimate ethical, legal, or confidentiality restrictions]. Access may be considered upon reasonable request and subject to applicable permissions."

E. Data Subject to an Embargo

"The dataset supporting this study has been deposited in [Repository Name] and is subject to an embargo until [date] for [state legitimate reason]."

F. No New Data Generated

"No new datasets were generated or analyzed during this study. Data sharing is therefore not applicable."

Authors must select and adapt the statement that accurately reflects the actual circumstances of their research.

4.3. Dataset Preparation and Documentation

Before sharing research data, authors should:

Verify data accuracy and completeness.
Remove or appropriately protect confidential information.
Organize datasets in understandable formats.
Provide clear variable names, definitions, and measurement units.
Describe coding schemes, missing values, and data transformations.
Include relevant methodological documentation.
Identify applicable licenses and access restrictions.
Provide persistent identifiers or stable access links where possible.

For livestock experiments, documentation should identify the experimental unit, treatment groups, observation periods, and other information necessary for interpreting the data.

4.4. Recommended Data Formats

Authors are encouraged to use widely accessible and well-documented file formats.

Examples include:

CSV or XLSX for tabular datasets.
TXT or other suitable formats for raw measurement records.
FASTQ, FASTA, or other established formats for biological sequence data.
R, Python, or other relevant scripts for computational analyses.
PDF or suitable text formats for protocols and documentation.

The choice of format should reflect the nature of the data and the standards of the relevant research community.

4.5. Peer-Review Assessment

Reviewers should evaluate whether the manuscript provides sufficient methodological and analytical detail to support its conclusions.

Where relevant, reviewers may consider:

Whether the experimental design is adequately described.
Whether the sample size and replication are appropriate.
Whether statistical methods are sufficiently explained.
Whether data exclusions or transformations are justified.
Whether supporting data are reasonably accessible.
Whether the Data Availability Statement is clear and accurate.
Whether the findings are consistent with the reported methods and results.

Reviewers are not expected to reproduce every analysis unless specifically requested and reasonably feasible.

4.6. Editorial Verification

The editorial office should verify that the manuscript includes the required data statement and that repository links or identifiers are provided where applicable.

Editors may request clarification if data access information is incomplete or inconsistent.

Where concerns arise regarding data integrity, the journal should follow its established publication ethics procedures.

4.7. Data Corrections and Updates

If errors are identified in a publicly shared dataset, authors should correct the data responsibly while preserving appropriate version information.

Where a dataset correction materially affects the published article, the authors must inform the journal.

The editorial team will determine whether a formal correction or another publication notice is required.

4.8. Long-Term Data Management

Authors are encouraged to use repositories and institutional data management systems that support stable access, secure storage, and appropriate preservation.

Research data preservation is distinct from the journal's preservation of published articles.

The journal's Archiving Policy addresses preservation of scholarly publications, while this policy addresses the responsible management and availability of underlying research data.

4.9. Policy Review and Improvement

The editorial team should periodically review this policy to reflect developments in data-sharing standards, repository infrastructure, research integrity guidance, and the needs of the livestock research community.

E-ISSN	3063-1912 (Online)
Publisher	LPPM Universitas Andalas
First Published	2024
Publication Frequency	2 issues per year (January and July)
DOI Prefix	10.25077/alive
OAI-PMH	View OAI-PMH